Triple
T9631445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Parc de la Francophonie |
E232811
|
entity |
| Predicate | hasCityContext |
P82630
|
FINISHED |
| Object | located in the historic core of Quebec City |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: located in the historic core of Quebec City | Statement: [Parc de la Francophonie, hasCityContext, located in the historic core of Quebec City]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCityContext Context triple: [Parc de la Francophonie, hasCityContext, located in the historic core of Quebec City]
-
A.
isInCity
Indicates that one entity is located within the geographical boundaries of a specified city.
-
B.
isInUrbanContext
chosen
Indicates that something exists, occurs, or is situated within an urban or city-based environment or setting.
-
C.
hasTargetCity
Indicates that something is directed toward, intended for, or specifically associated with a particular city as its target.
-
D.
hasComponentCity
Indicates that an entity includes or is composed of one or more cities as its constituent parts.
-
E.
hasCityRight
Indicates that an entity possesses legal or official rights associated with a particular city, such as jurisdiction, privileges, or authority within that city.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca848940cc8190b97cec654cb3bb4a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9b2621408190bfe2ea5a05359ee0 |
completed | April 1, 2026, 10:24 p.m. |
| PD | Predicate disambiguation | batch_69ccd5acfa5c8190aaba3cf548723604 |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:11 p.m.